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Possu Huang Lab @PossuHuangLab

Our lab uses experimental and computational methods to design de novo proteins | @Stanford

Joined October 2022
  • Tweets 108
  • Following 82
  • Followers 2,281
32 Photos and videos
Possu Huang Lab retweeted
The Mark Foundation for Cancer Research
@TheMarkFdn
Feb 3
Nikolaos Sgourakis, Mark Sellmyer (@sellmyerlab), & Possu Huang (@PossuHuangLab) are developing radioactive imaging agents to detect KRAS mutations, which drive 90% of pancreatic tumors but can’t currently be seen on scans. ☢️
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Possu Huang Lab retweeted
MLSB (in San Diego Copenhagen)@workshopmlsb
7 Dec 2025
Our next contributed talk is "Ensemble-conditioned protein sequence design with Caliby" by @richardwshuai
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Possu Huang Lab retweeted
Pauline Funchain@FunchainMD
4 Nov 2025
Ever wonder why our HLA specified cancer therapies are only for HLA02:01 thus far? @possuhuanglab presents the scope of the problem at the inaugural @StanfordCancer AI and Cancer Research Symposium 🧬 #AICancerResearch
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Possu Huang Lab retweeted
Richard Shuai@richardwshuai
3 Nov 2025
Excited by the growing interest in Caliby! Based on feedback from a few groups, we've downgraded some dependencies to support older OS versions. Please give it a try, and feel free to reach out with any issues github.com/ProteinDesignLab/…

GitHub - ProteinDesignLab/caliby: Potts model-based protein sequence design

Potts model-based protein sequence design. Contribute to ProteinDesignLab/caliby development by creating an account on GitHub.

github.com
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Possu Huang Lab retweeted
Nature Biotechnology
@NatureBiotech
29 Oct 2025
A protein platform rapidly develops peptide-focused major histocompatibility complex class I binders with high specificity go.nature.com/4gcLzn5 rdcu.be/eNagQ

Targeting peptide antigens using a multiallelic MHC I-binding system

Nature Biotechnology - A protein platform rapidly develops peptide-focused major histocompatibility complex class I binders with high specificity.

nature.com
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Possu Huang Lab retweeted
Nature Biotechnology
@NatureBiotech
28 Oct 2025
Specific binders to peptide–MHC class II are rapidly generated without laborious screening go.nature.com/4gj5OQk rdcu.be/eMYFS

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Possu Huang Lab retweeted
Nicole DelRosso@nicole_delrosso
24 Oct 2025
Tired of the bottleneck ⏳👔 between screening protein binders and actually measuring their affinities? Then check out our recent pre-print: biorxiv.org/content/10.1101/…

ADAPT-M: A workflow for rapid, quantitative in vitro measurements of enriched protein libraries

Protein-protein interactions underpin most cellular interactions, and engineered binders present powerful tools for probing biology and developing novel therapeutics. One bottleneck in binder...

biorxiv.org
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Interesting feature of the SLAE latent space ⬇️
Possu Huang Lab@PossuHuangLab
9 Oct 2025
Replying to @PossuHuangLab
SLAE projects all-atom structures onto a smooth manifold! Unguided linear interpolation between conformations in SLAE latent space decodes to coherent intermediates structures. (6/8)
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Introducing SLAE, our new framework to represent all-atom protein structures with residue local chemical environment tokens! SLAE reasons over atomic interactions to recover full structures and residue pairwise energetics, yielding a generalizable latent space. (1/8)
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Work done by @_YilinChen_, @Tianyu_Lu in the @PossuHuangLab, Cizhang Zhao and @HWaymentSteele. Thank you all! (7/8)
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Read our preprint here: biorxiv.org/content/10.1101/… (8/8)

SLAE: Strictly Local All-atom Environment for Protein Representation

Building physically grounded protein representations is central to computational biology, yet most existing approaches rely on sequence-pretrained language models or backbone-only graphs that...

biorxiv.org
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Possu Huang Lab retweeted
Richard Shuai@richardwshuai
6 Oct 2025
Excited to share Caliby 🐈, our new model for structure-conditioned sequence design! Caliby is a Potts model-based sequence design method that can condition on structural ensembles. We use this to average out non-structural signal (e.g. evolutionary bias) learned by models 🧵1/N
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💻Sampling and training code for Protpardelle-1c is now available: github.com/ProteinDesignLab/… Feedback and requests are welcome!

GitHub - ProteinDesignLab/protpardelle-1c: Updated Protpardelle models with more robust motif...

Updated Protpardelle models with more robust motif scaffolding and multichain support - ProteinDesignLab/protpardelle-1c

github.com
Possu Huang Lab@PossuHuangLab
19 Aug 2025
We have a new collection of protein structure generative models which we call Protpardelle-1c. It builds on the original Protpardelle and is tailored for conditional generation: motif scaffolding and binder generation.
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Possu Huang Lab retweeted
Hamed Khakzad@hamed_khakzad
20 Aug 2025
We were invited to write a preview about SHAPES, a great recent work from @PossuHuangLab. I really enjoyed this paper! It shows how far we still are from sampling the protein structural space without bias. Our preview just came out, check it out here: authors.elsevier.com/a/1ldzw…
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We have a new collection of protein structure generative models which we call Protpardelle-1c. It builds on the original Protpardelle and is tailored for conditional generation: motif scaffolding and binder generation.
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Our new set of all-atom models can sample plausible sidechains without stage-2 sampling. Sequence-dependent partial diffusion behavior occurs when we mask the dummy atoms.
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Code will be released soon on our GitHub: github.com/ProteinDesignLab/… Preprint: biorxiv.org/content/10.1101/… Have fun sampling and training!

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